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基于液滴的组织原位化学衍生化用于 LESA 分析的脂质异构体特征描述。

In situ droplet-based on-tissue chemical derivatization for lipid isomer characterization using LESA.

机构信息

Department of Chemistry, Texas A&M University, 580 Ross St, College Station, TX, 77843, USA.

Department of Nutrition, Texas A&M University, Carter-Mattil Hall, 373 Olven Blvd, College Station, TX, 77843, USA.

出版信息

Anal Bioanal Chem. 2023 Jul;415(18):4197-4208. doi: 10.1007/s00216-023-04653-3. Epub 2023 Apr 5.

DOI:10.1007/s00216-023-04653-3
PMID:37017722
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10392465/
Abstract

In this work, we present an in situ droplet-based derivatization method for fast tissue lipid profiling at multiple isomer levels. On-tissue derivatization for isomer characterization was achieved in a droplet delivered by the TriVersa NanoMate LESA pipette. The derivatized lipids were then extracted and analyzed by the automated chip-based liquid extraction surface analysis (LESA) mass spectrometry (MS) followed by tandem MS to produce diagnostic fragment ions to reveal the lipid isomer structures. Three reactions, i.e., mCPBA epoxidation, photocycloaddition catalyzed by the photocatalyst IrdF(CF)ppyPF, and Mn(II) lipid adduction, were applied using the droplet-based derivatization to provide lipid characterization at carbon-carbon double-bond positional isomer and sn-positional isomer levels. Relative quantitation of both types of lipid isomers was also achieved based on diagnostic ion intensities. This method provides the flexibility of performing multiple derivatizations at different spots in the same functional region of an organ for orthogonal lipid isomer analysis using a single tissue slide. Lipid isomers were profiled in the cortex, cerebellum, thalamus, hippocampus, and midbrain of the mouse brain and 24 double-bond positional isomers and 16 sn-positional isomers showed various distributions in those regions. This droplet-based derivatization of tissue lipids allows fast profiling of multi-level isomer identification and quantitation and has great potential in tissue lipid studies requiring rapid sample-to-result turnovers.

摘要

在这项工作中,我们提出了一种基于液滴的原位衍生化方法,用于快速在多个异构体水平上进行组织脂质分析。在组织上进行的异构体特征衍生化是通过 TriVersa NanoMate LESA 移液器提供的液滴来实现的。衍生化的脂质随后通过自动化芯片式液提取表面分析(LESA)质谱(MS)进行提取和分析,然后通过串联 MS 产生诊断片段离子以揭示脂质异构体结构。使用基于液滴的衍生化方法,应用了三种反应,即 mCPBA 环氧化、光催化剂 IrdF(CF)ppyPF 催化的光环加成反应以及 Mn(II)脂质加成反应,以提供碳-碳双键位置异构体和 sn-位置异构体水平的脂质特征。还基于诊断离子强度实现了两种类型的脂质异构体的相对定量。该方法提供了在同一器官的功能区域的不同点进行多种衍生化的灵活性,可用于使用单个组织载玻片进行正交脂质异构体分析。对小鼠大脑的皮质、小脑、丘脑、海马和中脑进行了脂质异构体分析,在这些区域中,24 个双键位置异构体和 16 个 sn-位置异构体显示出不同的分布。这种组织脂质的基于液滴的衍生化允许快速进行多层次异构体的鉴定和定量分析,在需要快速样品到结果转换的组织脂质研究中具有很大的潜力。